scholarly journals Design of Low-Cost Vehicle Roll Angle Estimator Based on Kalman Filters and an IoT Architecture

Sensors ◽  
2018 ◽  
Vol 18 (6) ◽  
pp. 1800 ◽  
Author(s):  
Javier Garcia Guzman ◽  
Lisardo Prieto Gonzalez ◽  
Jonatan Pajares Redondo ◽  
Susana Sanz Sanchez ◽  
Beatriz Boada
Keyword(s):  
Kalman Filters ◽  
Low Cost ◽  
Roll Angle

scholarly journals A Novel Roll and Pitch Estimation Approach for a Ground Vehicle Stability Improvement Using a Low Cost IMU

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 340 ◽  
Author(s):  
Malik Kamal Mazhar ◽  
Muhammad Jawad Khan ◽  
Aamer Iqbal Bhatti ◽  
Noman Naseer
Keyword(s):  
Kalman Filters ◽  
Sliding Mode ◽  
Low Cost ◽  
Warning Signal ◽  
Stability Control ◽  
Attitude Estimation ◽  
Roll Angle ◽  
Measurement Unit ◽  
Second Phase ◽  
Ground Vehicle

Onboard attitude estimation for a ground vehicle is persuaded by its application in active anti-roll bar design. Conventionally, the attitude estimation problem for a ground vehicle is a complex one, and computationally, its solution is very intensive. Lateral load transfer is an important parameter which should be taken in account for all roll stability control systems. This parameter is directly related to vehicle roll angle, which can be measured using devices such as dual antenna global positioning system (GPS) which is a costly technique, and this led to the current work in which we developed a simple and robust attitude estimation technique that is tested on a ground vehicle for roll mitigation. In the first phase Luenberger and Sliding mode observer is implemented using simplest roll dynamics model to measure the roll angle of a vehicle and the validation of results is carried using commercial software, CarSim® (CarSim, Ann Arbor, MI, USA). In the second phase of research, complementary and Kalman filters have been designed for attitude estimation. In the third phase, a low-cost inertial measurement unit (IMU) is mounted on a vehicle, and both the complementary filter (CF) and Kalman filter (KF) are applied independently to measure the data for both smooth and uneven terrains at four different frequencies. We compared the simulated and real-time results of roll and pitch angles obtained using the complementary and Kalman filters. Using the proposed method, the achieved root mean square error (RMSE) is less than 0.73 degree for pitch and 0.68 degree for roll, with a sample time of 2 ms. Thus, a warning signal can be generated to mitigate roll over. Hence, we claim that our proposed method can provide a low-cost solution to the roll-over problem for a road vehicle.

scholarly journals A Low-Cost MEMS Missile-Borne Compound Rotation Modulation Scheme

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4910
Author(s):  
Xiaoqiao Yuan ◽  
Jie Li ◽  
Xi Zhang ◽  
Kaiqiang Feng ◽  
Xiaokai Wei ◽  
...  
Keyword(s):  
Rotation Axis ◽  
Low Cost ◽  
Roll Angle ◽  
Modulation Scheme ◽  
Navigation Systems ◽  
Rotation Scheme ◽  
Compound Rotation ◽  
Error Accumulation ◽  
Axis Rotation ◽  
Single Axis Rotation

Rotation modulation (RM) has been widely used in navigation systems to significantly improve the navigation accuracy of inertial navigation systems (INSs). However, the traditional single-axis rotation modulation cannot achieve the modulation of all the constant errors in the three directions; thus, it is not suitable for application in highly dynamic environments due to requirements for high precision in missiles. Aiming at the problems of error accumulation and divergence in the direction of rotation axis existing in the traditional single-axis rotation modulation, a novel rotation scheme is proposed. Firstly, the error propagation principle of the new rotation modulation scheme is analyzed. Secondly, the condition of realizing the error modulation with constant error is discussed. Finally, the original rotation modulation navigation algorithm is optimized for the new rotation modulation scheme. The experiment and simulation results show that the new rotation scheme can effectively modulate the error divergence of roll angle and improve the accuracy of roll angle by two orders of magnitude.

scholarly journals Real-time Vehicle Roll Angle Estimation based on IoT low-cost devices and Neural Networks

2018 ◽  
Author(s):  
Javier Garcia-Guzman ◽  
Lisardo Prieto González ◽  
Jonatan Pajares Redondo ◽  
Mat Max Montalvo Martinez ◽  
María Jesús López Boada
Keyword(s):  
Neural Networks ◽  
Real Time ◽  
Low Cost ◽  
Roll Angle ◽  
Measurement Unit ◽  
Raspberry Pi ◽  
State Variables ◽  
Angle Estimation ◽  
Experimental Environment ◽  
Time Operation

Given the high number of vehicle-crash victims, it has been established as a priority to reduce this figure in the transportation sector. For this reason, many of the recent researches are focused on including control systems in existing vehicles, to improve their stability, comfort and handling. These systems need to know in every moment the behavior of the vehicle (state variables), among others, when the different maneuvers are performed, to actuate by means of the systems in the vehicle (brakes, steering, suspension) and, in this way, to achieve a good behavior. The main problem arises from the lack of ability to directly capture several required dynamic vehicle variables, such as roll angle, from low-cost sensors. Previous studies demonstrate that low-cost sensors can provide data in real-time with the required precision and reliability. Even more, other research works indicate that neural networks are efficient mechanisms to estimate roll angle. Nevertheless, it is necessary to assess that the fusion of data coming from low-cost devices and estimations provided by neural networks can fulfill the reliability and appropriateness requirements for using these technologies to improve overall safety in production vehicles. Because of the increasing of computing power, the reduction of consumption and electric devices size, along with the high variety of communication technologies and networking protocols using Internet have yield to Internet of Things (IoT) development. In order to address this issue, this study has two main goals: 1) Determine the appropriateness and performance of neural networks embedded in low-cost sensors kits to estimate roll angle required to evaluate rollover risk situations. 2) Compare the low-cost control unit devices (Intel Edison and Raspberry Pi 3 Model B), to provide the roll angle estimation with this artificial neural network-based approach. To fulfil these objectives an experimental environment has been set up composed of a van with two set of low-cost kits, one including a Raspberry Pi 3 Model B, low cost Inertial Measurement Unit (BNO055 - 37€) and GPS (Mtk3339 - 53€) and the other having an Intel Edison System on Chip linked to a SparkFun 9 Degrees of Freedom module. This experimental environment will be tested in different maneuvers for comparison purposes. Neural networks embedded in low-cost sensor kits provide roll angle estimations very approximated to real values. Even more, Intel Edison and Raspberry Pi 3 Model B have enough computing capabilities to successfully run roll angle estimation based on neural networks to determine rollover risks situation fulfilling real-time operation restrictions stated for this problem.

scholarly journals Comparison of Kalman Filters for Inertial Integrated Navigation

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1426 ◽  
Author(s):  
Mengde Zhang ◽  
Kailong Li ◽  
Baiqing Hu ◽  
Chunjian Meng
Keyword(s):  
Navigation System ◽  
Kalman Filters ◽  
Inertial Navigation System ◽  
Low Cost ◽  
Inertial Navigation ◽  
Strapdown Inertial Navigation System ◽  
Integrated Navigation ◽  
Filtering Algorithms ◽  
Navigation Equipment ◽  
Navigation Filters

The current research on integrated navigation is mainly focused on filtering or integrated navigation equipment. Studies systematically comparing and analyzing how to choose appropriate integrated filtering methods under different circumstances are lacking. This paper focuses on integrated navigation filters that are used by different filters and attitude parameters for inertial integrated navigation. We researched integrated navigation filters, established algorithms, and examined the relative merits for practical integrated navigation. Some suggestions for the use of filtering algorithms are provided.We completed simulations and car-mounted experiments for low-cost strapdown inertial navigation system(SINS) to assess the performance of the integrated navigation filtering algorithms.

Roll angle estimation using low cost MEMS sensors for paddy field machine

2019 ◽  
Vol 158 ◽  
pp. 183-188 ◽  
Author(s):  
Lian Hu ◽  
Weiwei Yang ◽  
Jing He ◽  
Hao Zhou ◽  
Zhigang Zhang ◽  
...  
Keyword(s):  
Paddy Field ◽  
Low Cost ◽  
Roll Angle ◽  
Mems Sensors ◽  
Angle Estimation

GPS-Free Terrain-Based Vehicle Tracking Performance as a Function of Inertial Sensor Characteristics

2011 ◽  
Author(s):  
Kshitij Jerath ◽  
Sean N. Brennan
Keyword(s):  
Kalman Filters ◽  
Inertial Sensors ◽  
Inertial Sensor ◽  
Low Cost ◽  
Tracking Error ◽  
Vehicle Tracking ◽  
Tracking Performance ◽  
Tracking Accuracy ◽  
Localization Algorithms ◽  
Bias Instability

Prior experiments have confirmed that specific terrain-based localization algorithms, designed to work in GPS-free or degraded-GPS environments, achieve vehicle tracking with tactical-grade inertial sensors. However, the vehicle tracking performance of these algorithms using low-cost inertial sensors with inferior specifications has not been verified. The included work identifies, through simulations, the effect of inertial sensor characteristics on vehicle tracking accuracy when using a specific terrain-based tracking algorithm based on Unscented Kalman Filters. Results indicate that vehicle tracking is achievable even when low-cost inertial sensors with inferior specifications are used. However, the precision of vehicle tracking decreases approximately linearly as bias instability and angle random walk coefficients increase. The results also indicate that as sensor cost increases, the variance in vehicle tracking error asymptotically tends to zero. Put simply, as desired precision increases, increasingly larger and quantifiable investment is required to attain an improvement in vehicle tracking precision.

scholarly journals Real-Time Vehicle Roll Angle Estimation Based on Neural Networks in IoT Low-Cost Devices

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2188 ◽  
Author(s):  
Javier García Guzmán ◽  
Lisardo Prieto González ◽  
Jonatan Pajares Redondo ◽  
Mat Montalvo Martínez ◽  
María L. Boada
Keyword(s):  
Neural Networks ◽  
Real Time ◽  
Low Cost ◽  
Roll Angle ◽  
Angle Estimation

Real-Time Roll Angle Estimation for Two-Wheeled Vehicles

2012 ◽  
Author(s):  
Roberto Lot ◽  
Vittore Cossalter ◽  
Matteo Massaro
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Simulated Data ◽  
Time Estimation ◽  
Real Data ◽  
Original Method ◽  
Roll Angle ◽  
Collision Warning ◽  
Multibody Model ◽  
Wheeled Vehicles

An original method for the real-time estimation of the roll angle using low-cost sensors in two-wheeled vehicles is proposed. The roll angle greatly affects the dynamics of single-track vehicles and its estimation is essential in control systems such as ABS, Traction Control, as well as Curve and Collision Warning, or even active suspensions. The proposed method uses a non-linear Kalman filter, its performances are assessed by using both a set of simulated data from a multibody model and a set of real data collected on an instrumented test vehicle.

Decomposition of the metastable beta titanium alloy Ti-15-3

1983 ◽  
Vol 41 ◽  
pp. 264-265
Author(s):  
Y. L. Chen ◽  
S. Fujlshiro
Keyword(s):  
Low Cost ◽  
High Strength ◽  
Alpha Phase ◽  
Thick Sheet ◽  
Omega Phase ◽  
Beta Titanium Alloy ◽  
Beta Titanium ◽  
Beta Matrix ◽  
Metastable Beta ◽  
Very High

Metastable beta titanium alloys have been known to have numerous advantages such as cold formability, high strength, good fracture resistance, deep hardenability, and cost effectiveness. Very high strength is obtainable by precipitation of the hexagonal alpha phase in a bcc beta matrix in these alloys. Precipitation hardening in the metastable beta alloys may also result from the formation of transition phases such as omega phase. Ti-15-3 (Ti-15V- 3Cr-3Al-3Sn) has been developed recently by TIMET and USAF for low cost sheet metal applications. The purpose of the present study was to examine the aging characteristics in this alloy.The composition of the as-received material is: 14.7 V, 3.14 Cr, 3.05 Al, 2.26 Sn, and 0.145 Fe. The beta transus temperature as determined by optical metallographic method was about 770°C. Specimen coupons were prepared from a mill-annealed 1.2 mm thick sheet, and solution treated at 827°C for 2 hr in argon, then water quenched. Aging was also done in argon at temperatures ranging from 316 to 616°C for various times.

Chromic Acid Etching of Polyethylene

1973 ◽  
Vol 31 ◽  
pp. 72-73
Author(s):  
J. D. Muzzy ◽  
R. D. Hester ◽  
J. L. Hubbard
Keyword(s):  
Chromic Acid ◽  
Low Cost ◽  
Acid Etching ◽  
Crystalline Morphology ◽  
Bulk Specimen ◽  
Morphological Studies ◽  
Perfect Form ◽  
Molecular Length ◽  
Lamellar Texture ◽  
Cost Studies

Polyethylene is one of the most important plastics produced today because of its good physical properties, ease of fabrication and low cost. Studies to improve the properties of polyethylene are leading to an understanding of its crystalline morphology. Polyethylene crystallized by evaporation from dilute solutions consists of thin crystals called lamellae. The polyethylene molecules are parallel to the thickness of the lamellae and are folded since the thickness of the lamellae is much less than the molecular length. This lamellar texture persists in less perfect form in polyethylene crystallized from the melt.Morphological studies of melt crystallized polyethylene have been limited due to the difficulty of isolating the microstructure from the bulk specimen without destroying or deforming it.

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